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Related Experiment Video

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An automated ASPECTS method with atlas-based segmentation.

Zechen Yu1, Zhongping Chen2, Yang Yu2

  • 1Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China; Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing 210096, China.

Computer Methods and Programs in Biomedicine
|September 9, 2021
PubMed
Summary

An automated method for evaluating early ischemic changes in acute ischemic stroke (AIS) patients using non-contrast computed tomography (NCCT) shows promise. This auto-ASPECTS approach improves diagnostic accuracy and aids in treatment decisions.

Keywords:
ASPECTSAcute ischemic strokeAutomated methodNCCT

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Area of Science:

  • Neuroradiology
  • Medical Imaging Analysis
  • Stroke Diagnostics

Background:

  • Alberta Stroke Program Early CT score (ASPECTS) is a standard for evaluating ischemic stroke but suffers from inter-reader variability.
  • Accurate and timely assessment of early ischemic changes is crucial for treatment selection and prognosis in acute ischemic stroke (AIS).

Purpose of the Study:

  • To develop and validate an automated semi-quantitative method (auto-ASPECTS) for diagnosing acute ischemic stroke using non-contrast computed tomography (NCCT).
  • To provide an objective reference for doctors in the diagnosis and evaluation of early ischemic changes.

Main Methods:

  • Non-contrast computed tomography (NCCT) data from 90 patients were used for training and testing the auto-ASPECTS system.
  • Atlas-based segmentation was employed to define regions of interest for ASPECTS.
  • Brain density shifts (BDS) of contralateral brain regions were utilized as a quantitative standard for analysis.

Main Results:

  • The auto-ASPECTS method using Brain Density Shifts (BDS) achieved an accuracy of 0.80 in the test set.
  • Using different BDS thresholds improved accuracy by 6.67% compared to a consistent threshold.
  • The agreement between dichotomized auto-ASPECTS and consensus scores was 83.3%.

Conclusions:

  • The proposed automated ASPECTS method for NCCT images offers valuable information for the early diagnosis and evaluation of acute ischemic stroke (AIS).
  • This automated approach can assist clinicians in making more consistent and accurate assessments of ischemic stroke severity.